International Business Machines Corporation

Jae-Wook Ahn

Patrick D Watson

Maria Chang

Sharad C Sundararajan

Ravindranath Kokku

Ravi Tejwani

Mudhakar Srivatsa

Raghu Kiran Ganti

Tengfei Ma

Shreeranjani Srirangamsridharan

Dinesh C Verma

Douglas Morgan Freimuth

Seraphin Bernard Calo

Prasenjit Dey

Brian Leo Quanz

Nirmit V Desai

Pin-Yu Chen

Tova Roth

Aldis G Sipolins

Payel Das

Michele Merler

Nirmal K Mukhi

Renuka Sindhgatta

Steven A Waite

Vinay Kumar Reddy Kasireddy

Cassius D'Helon

Shazia Afzal

Dean Steuer

Sharad Chandra Sundararajan

Roger Hollander

Anshu Kak

Methods and systems for emulating an application include generating a log template to match one or more patterns in a set of application logs collected from an original application. Semantic state representations are learned for the original application from the log template. A classifier is trained to predict a next action template based on a sequence of prior action templates. A regressor is trained to generate a parameter value for a template based on a sequence of prior action templates and a particular semantic state of the original application.

Machine learning to emulate software applications

Systems, methods and/or computer program products for controlling and visualizing topic modeling results using a topic modeling interface. The interface allows user directed exploration, understanding and control of topic modeling algorithms, while offering both semantic summaries and/or structure attribute explanations about results. Explanations and differentiations between results are presented using metrics such as cohesiveness and visual displays depicting hierarchical organization. Through user-manipulation of features of the interface, iterative changes are implemented through user-feedback, adjusting parameters, broadening or narrowing topic results, and/or reorganizing topics by splitting or merging topics. As users trigger visual changes to results being displayed, users can compare and contrast output from the topic modeling algorithm. With each change to parameters, users view different explanations informing the user why the changes being displayed occurred, providing users deeper understanding of the topic modeling process, how to manipulate parameters to achieve accurate topic results and adjust granularity of information presented.

Transparent and controllable topic modeling

Embodiments relate to a system, program product, and method for inducing creativity in an artificial neural network (ANN) having an encoder and decoder. Neurons are automatically selected and manipulated from one or more layers of the encoder. An encoded vector is sampled for an encoded image. Decoder neurons and a corresponding activation pattern are evaluated with respect to the encoded image. The decoder neurons that correspond to the activation pattern are selected, and an activation setting of the selected decoder neurons is changed. One or more novel data instances are automatically generated from an original latent space of the selectively changed decoder neurons.

Inducing creativity in an artificial neural network

A method for obtaining information and status about a monitored system by adaptively analyzing log messages is provided. A log analyzer receives log messages generated by a monitored system. The log analyzer identifies static and variable portions in the received log messages. The log analyzer generates a template based on the identified static and variable portions of the received log messages. The log analyzer computes a metric for the generated template based on a number of log messages that fall within the template. The log analyzer reports a status in the monitored system based on the computed metric.

Adaptive log analysis

Techniques for assessing the proficiency of artificial intelligence agents and users in a given knowledge domain are described. A plurality of proficiency agents can be initialized with a plurality of proficiency scores, by performing a plurality of assessments between pairs of proficiency agents selected from the plurality of proficiency agents. A first client device associated with a first user is matched with a first proficiency agent of the plurality of proficiency agents, based on a first proficiency score associated with the first user and a second proficiency score of the plurality of proficiency scores corresponding to the first proficiency agent. Assessments results of an assessment performed between the first client device and the first proficiency agent are received, and a rating system update function is used to update the first proficiency score and the second proficiency score, based on the assessment results.

Modeling mastery in distributed cognitive systems and storing the results in a ledger

Systems, methods, and computer program products to perform an operation comprising receiving text input via a chat interface of a tutor application, identifying, by at least one classifier applied to the text input, a concept in the text input, mapping the concept in the text input to at least one of a visual action and a first visual object, generating, based on a first machine learning (ML) model, a first program code statement corresponding to the at least one of the visual action and the first visual object, and executing the first program code statement to modify a visualization interface of the tutor application based on the text input received via the chat interface.

Enhanced visual dialog system for intelligent tutors

A method and system of providing education content to a student is provided. A topic to be taught to a student is received. A user model of the student is identified. An electronic content model for the topic is determined. One or more presentation templates are identified based on the electronic content model. A concept map is determined based on the one or more presentation templates. A presentation template is selected from the one or more presentation templates. A segment of an educational content of the topic is provided to a user device of the student, based on the selected presentation template.

Adaptive presentation of educational content via templates

Improving performance of a dialogue-based tutor includes receiving feedback from a user associated with a natural language interaction of the user with a dialogue-based tutoring (DBT) system. The DBT system includes training data and domain-specific content. One or more feedback categories is presented to the user based upon the feedback. A selection of a feedback category from among the one or more feedback categories is received from the user. A feedback candidate is generated based upon the feedback and the selected feedback category. The feedback candidate is indicative of a potential change in one or more of the training data and the domain-specific content based upon the feedback.

Feedback system and method for improving performance of dialogue-based tutors

Method and apparatus for generating natural language observations using sequence-to-sequence models are provided. The method includes receiving a first electronic document and dynamically generating, without requiring user intervention, a first natural language observation corresponding to a first portion of the first electronic document by processing the first portion of the first electronic document using a first sequence-to-sequence model. A second natural language observation is received for the first portion of the first electronic document, and the generated first natural language observation and the authoritative natural language observation are provided. The method further includes receiving an evaluation of the first natural language observation and the second natural language observation, and refining the first sequence-to-sequence model based on the evaluation of the first natural language observation and second natural language observation.

Distributed system for evaluation and feedback of digital text-based content

A method for authenticating a user is presented. Responsive to a request for access to a computer resource, a computer system prompts the user making the request to access the computer resource to perform a new motion in an environment in which the user is monitored by a sensor system. Detected biometric data in the new motion performed by the user is identified by the computer system. A determination is made as to whether the user performing the new motion is an authenticated user based on comparing the detected biometric data with stored biometric data for a prior motion performed by the authenticated user. The computer system provides access to the computer resource when the user is identified as the authenticated user.

Motion based authentication

A method and system of interactive tutoring is provided. A question is sent to a user device. Upon determining that the response does not correspond to a known correct answer, a concept map is identified and a cost function between the correct answer and the response is determined. Upon determining that the cost function between the correct answer and the response is above a predetermined threshold, the question is identified to be the origin. Otherwise, the response is identified to be the origin. A present academic proficiency of the student is determined. A difficulty boundary based on the academic proficiency of the student is determined. A next question is provided between the origin and the correct answer, based on the determined difficulty boundary of the student.

Providing partial answers to users

Techniques facilitating using a blockchain system that integrates the trustworthiness of the blockchain concept with open scientific research by generating a blockchain of the experiments formed, data collected, analyses performed, and results achieved are provided herein. In an example, the blockchain system can form a blockchain representing a research project, wherein the blockchain comprises a first block of research data and a second block of analysis data representing a log of an analysis performed on the research data. Summary blocks and correction blocks can also be added to the blockchain representing the post analysis of the research results. One or more of the subsequent blocks can be linked to the preceding blocks using information in block headers that can also serve to determine whether modifications to the blocks have been performed.

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Nanuet, NY, United States of America

Jae-Wook Ahn